Evidence map›Paper›PMID 30527314›Full record

ArticleEuropean journal of radiology2018

Automated image analysis tool for tumor volume growth rate to guide precision cancer therapy: EGFR-mutant non-small-cell lung cancer as a paradigm.

Mizuki Nishino, Satoshi Wakai, Tomoyuki Hida, Suzanne E Dahlberg, Masahiro Ozaki, Hiroto Hatabu, Hisashi Tachizaki, Bruce E Johnson

Abstract read
In one paragraph

Article in European journal of radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Tumor volume dynamics and tumor growth rate inEuropean journal of radiology open · 2020
    Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Mizuki NishinoDepartment of Radiology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02215, USA. Electronic address: Mizuki_Nishino@DFCI.HARVARD.EDU.
Satoshi WakaiCanon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi 324-8550, Japan.
Tomoyuki HidaDepartment of Radiology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02215, USA.
Suzanne E DahlbergDepartment of Biostatistics, Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02215, USA.
Masahiro OzakiCanon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi 324-8550, Japan.
Hiroto HatabuDepartment of Radiology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02215, USA.
Hisashi TachizakiCanon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi 324-8550, Japan.
Bruce E JohnsonDepartment of Medical Oncology and Department of Medicine, Dana-Farber Cancer Institute and Brigham and Women's Hospital, 450 Brookline Ave., Boston, MA 02215, USA.
Dana-Farber Cancer Institute · USCanon Medical Systems Corporation (Japan)Brigham and Women's Hospital · US

Funding

Automated in vivo analysis of tumor growth rate as a guide for therapeutic decisions to advance personalized cancer treatmentR01CA203636 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI NISHINO, MIZUKI · 2017 to 2021
$2.9M
NCI NIH HHS R01 CA203636
6 · The paper itself

Abstract

purposeTo develop an automated analytic module for calculation of tumor growth rate from serial CT scans and to apply the module and evaluate reproducibility in a pilot cohort of advanced NSCLC patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors. MATERIALS AND

methodsThe module utilized a commercially available image-processing workstation equipped with a validated tumor volume measurement tool. An automated analytic software module was programmed with the capability to record and display serial tumor volume changes and to calculate tumor volume growth rate over time and added to the workstation. The module was applied to evaluate the tumor growth rate in a pilot cohort of 24 EGFR-mutant patients treated with EGFR inhibitors, and reproducibility references as tested by two independent thoracic radiologists.

resultsThe module analyzed chest CT scans from 24 patients (5 males, 19 females; median age: 61) with a median of 8 scans per patient, totaling 227 scans and provided a graphical display with an automated and instant calculation of tumor growth rate after the nadir volume for each patient. High inter and intraobserver agreements were noted for tumor growth rates, with concordance correlation coefficients of 0.9323 and 0.9668, respectively. Interpretation of slow versus fast tumor growth using previously identified threshold of ≤0.15/month had a perfect interobserver agreement (κ = 1.00), and an excellent intraobserver agreement (κ = 0.895).

conclusionsThe present study describes the development of an image analytic module for assessing tumor growth rate and the data demonstrates the functionality and reproducibility of the module in a pilot cohort of EGFR-mutant NSCLC patients treated with EGFR-TKI. The image analytic module is an initial step for clinical translation of the tumor growth rate approach to guide cancer treatment in precision oncology.

Indexed as

Carcinoma, Non-Small-Cell LungCohort StudiesErbB ReceptorsFemaleHumansLung NeoplasmsMaleMiddle AgedMutationPrecision MedicineProtein Kinase InhibitorsReproducibility of ResultsTomography, X-Ray ComputedTumor BurdenEGFR protein, humanErbB ReceptorsProtein Kinase InhibitorsComputed tomographyEGFR inhibitorEpidermal growth factor receptorLung cancerTumor growth rate

Identifiers

PMID30527314
PMCPMC6294464
OpenAlexW2897407530

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.